A growing number of social science researchers, including educational researchers, have turned to online crowdsourcing platforms such as Prolific and MTurk for their experiments. However, there is a lack of research investigating the quality of data generated by online subjects and how they compare with traditional subject pools of college students in studies that involve cognitively demanding tasks. Using an interactive problem-solving task embedded in an educational simulation, we compare the task engagement and performance based on the interaction log data of college students recruited from Prolific to those from an introductory physics course. Results show that Prolific participants performed on par with participants from the physics class in obtaining the correct solutions. Furthermore, the physics course students who submitted incorrect answers were more likely than Prolific participants to make rushed cursory attempts to solve the problem. These results suggest that with thoughtful study design and advanced learning analytics and data mining techniques, crowdsourcing platforms can be a viable tool for conducting research on teaching and learning in higher education.
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Wang et al. (2024) studied this question.
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